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Problem Algorithm

WebCab Optimization (J2EE Edition) 2.6

WebCab Optimization (J2EE Edition) 2.6: Enterprise Java Component for solving local or global optimization problems. algorithms based on the Simplex Algorithm and duality are included along with a framework for sensitivity analysis w.r.t. boundaries (duality, or direct approach), or object function coefficients. This suite includes the following features: local unidimensional optimization; fast `low level ` algorithms where the weight is on speed and not the accuracy of the results; bracketing algorithms - these methods find an interval where at least one extrema






JOpt.SDK - route optimization library 2.1.0: resource and  transportation planning, route planning and optimization library
JOpt.SDK - route optimization library 2.1.0

JOpt.SDK is a route optimization and planning Java library for automatic resource scheduling and transportation planning. It uses specialized genetic algorithms to calculate an optimized allocation of orders and stops to mobile resources. JOpt.SDK can solve problems like TSP (travelling salesman problem) or VRPTW (vehicle routing problem).

vehicle routing problem, travelling salesman problem, tour optimization, tour planning, genetic algorithms, resource scheduling, logistics, route optimization, vrptw, transportation





JOpt.SDK - vehicle routing library 4.0.6: resource and  transportation planning, route planning and optimization library
JOpt.SDK - vehicle routing library 4.0.6

JOpt.SDK is a route optimization and planning Java library for automatic resource scheduling and transportation planning. It uses specialized genetic algorithms to calculate an optimized allocation of orders and stops to mobile resources. JOpt.SDK can solve problems like TSP (travelling salesman problem) or VRPTW (vehicle routing problem).

vehicle routing problem, travelling salesman problem, tour optimization, tour planning, genetic algorithms, resource scheduling, logistics, route optimization, vrptw, transportation



Inventive Problem Solving Software 2.0: ARIZ - Inventive Problem Solving Software (Strategy, Management, Creativity, Inn
Inventive Problem Solving Software 2.0

Algorithm of Inventive Problems Solving (ARIZ) is list of (about 85) step-by-step procedures that incrementally evolves a complex problem to a point where it is simple to solve. Complex problems cannot be solved in just two steps. For those problems which are so complex, that they cannot be solved with any other tools, TRIZ includes the algorithm to follow which will facilitate the problem-solving process. ARIZ is not an equation, but rather a multi

creativity, software, problem, ariz, innovation, strategy, solving, inventive, management



Inventive Problem Solving Software 2.0: ARIZ - Inventive Problem Solving Software (Strategy, Management, Creativity, Inn
Inventive Problem Solving Software 2.0

Algorithm of Inventive Problems Solving (ARIZ) is list of (about 85) step-by-step procedures that incrementally evolves a complex problem to a point where it is simple to solve. Complex problems cannot be solved in just two steps. For those problems which are so complex, that they cannot be solved with any other tools, TRIZ includes the algorithm to follow which will facilitate the problem-solving process. ARIZ is not an equation, but rather a multi

creativity, software, problem, ariz, innovation, strategy, solving, inventive, management



Simulated Annealing Demonstration 1.0: This is a Java application that demonstrates the Simulated Annealing algorithm.
Simulated Annealing Demonstration 1.0

This is a Java application that demonstrates the Simulated Annealing algorithm with an attack on the "traveling salesman" problem. What is simulated annealing? Simulated annealing is a technique, which was developed to help solve large combinatorial optimization problems. It is based on probabilistic methods that avoid being stuck at local (non-global) minima.

annealing, salesman, traveling, simulated



FindDec standard 1.0.1.77: FindDec search of global and local optimums at system of functions
FindDec standard 1.0.1.77

algorithm. FindDec is available in three versions: Standard, Professional, and Unlimited. The number of variables in the FindDec standard must be no more than 70. FindDec solves maximum/minimum optimization problem in finance, distribution, scheduling, resource allocation, manufacturing, budgeting, engineering, and more. FindDec can find optimal solutions to problems which are "unsolvable" for standard linear and non-linear optimizers. FindDec can

system of function, optimization problem, local optimum, global optimum, search of optimums


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